Using artificial intelligence, researchers show how γ-secretase recognizes substrates - an important advance for fundamental ...

Coinbase and Perplexity AI team up to deliver real-time crypto market data and AI-driven insights—redefining how traders and ...

Researchers from DZNE, Ludwig-Maximilians-Universität München (LMU), and Technical University of Munich (TUM) have found that ...

Explainable AI (XAI) is an emerging field in machine learning that aims to address how black box decisions of AI systems are made. This area inspects and tries to understand the steps and models ...

Civic engagement platforms (CEPs) are online infrastructures that facilitate democratic dialogue, community decision-making, ...

As tech writer Scott Clark noted on CMSWire recently, explainable AI provides necessary insight into the decision-making process to allow users to understand why it is behaving the way it is.

A Future with Explainable AI. Explainable AI is the future of business decision-making. Explainable decision making plays a role in every aspect of AI solutions from training, QA, deployment, ...

Explainable AI addresses this limitation by providing insight into the model’s decision-making process,” the Virginia Tech team notes. The study authors actually created and tested an MPEA ...

An explainable AI yields two pieces of information: its decision and the explanation of that decision. This is an idea that has been proposed and explored before. However, ...

In it, explainable AI is placed at the peak of inflated expectations. In other words, we have reached peak hype for explainable AI. To put that into perspective, a recap may be useful.

Why explainable AI matters. According to a report released by KPMB and Forrester Research last year, only 21 percent of US executives have a high level of trust in their analytics. “And that’s ...